using excel>data>data analysis>Regression
we have
| SUMMARY OUTPUT | ||||||
| Regression Statistics | ||||||
| Multiple R | 0.39411 | |||||
| R Square | 0.155322 | |||||
| Adjusted R Square | 0.049738 | |||||
| Standard Error | 2.736047 | |||||
| Observations | 10 | |||||
| ANOVA | ||||||
| df | SS | MS | F | Significance F | ||
| Regression | 1 | 11.01236 | 11.01236 | 1.471069 | 0.259773 | |
| Residual | 8 | 59.88764 | 7.485955 | |||
| Total | 9 | 70.9 | ||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
| Intercept | 16.8427 | 1.677222 | 10.04202 | 8.23E-06 | 12.97502 | 20.71038 |
| Minutes | -0.37079 | 0.305708 | -1.21288 | 0.259773 | -1.07575 | 0.334178 |
a ) option C is true
t = -1.21
p value = 0.260
since p value is greater than 0.05, the regression slope is not significant .
b ) LCL =-1.08
UCL = 0.334
please provide droplets for part c in comment box
A customer service department and is customers to sate their own the phone service on a...
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Customer Service Department
Data Inputs
Resource Data:
Number of employees
24
Average salary per employee
$
37,710
Weeks of employment per year
50
Minutes available per week (40 hours × 60 minutes)
2,400
Practical capacity percentage
90
%
Activity Data:
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Processing Credit Reviews
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